class_docstr: Construct a CoreML KNearestNeighborsClassifier specification.
  
  Please see the Core ML Nearest Neighbors protobuf message for more information
  on KNearestNeighborsClassifier parameters.
  
  Examples
  --------
  .. sourcecode:: python
  
      from coremltools.models.nearest_neighbors import KNearestNeighborsClassifierBuilder
      from coremltools.models.utils import save_spec
  
      # Create a KNearestNeighborsClassifier model that takes 4-dimensional input data and outputs a string label.
      >>> builder = KNearestNeighborsClassifierBuilder(input_name='input',
      ...                                              output_name='output',
      ...                                              number_of_dimensions=4,
      ...                                              default_class_label='default_label')
  
      # save the spec by the builder
      >>> save_spec(builder.spec, 'knnclassifier.mlmodel')
      
docstr: Checks if the object is a valid text type.
  
  Parameters
  ----------
  obj
          The object to check.
  
  Returns
  -------
  True if a valid text type, False otherwise.
docstr_tok: ["Checks","if","the","object","is","a","valid","text","type",".","Parameters","--","--","--","--","--","obj","The","object","to","check",".","Returns","--","--","--","-","True","if","a","valid","text","type",",","False","otherwise","."]
code: def _is_valid_text_type(obj):
      """
      Checks if the object is a valid text type.
  
      Parameters
      ----------
      obj
              The object to check.
  
      Returns
      -------
      True if a valid text type, False otherwise.
      """
      return isinstance(obj, str)
  
imports: import numpy
  import coremltools
  from ...proto import FeatureTypes_pb2
  from ..None import datatypes
label_desc: Use image node_id 23 for calling the KNearestNeighborsClassifierBuilder obj's underlying member method code with example usage: obj._is_valid_text_type(obj) and returns: isinstance